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ai-platform-audit

Review AI, retrieval, agent, and MCP systems for grounding, evaluation, permissions, privacy, observability, and cost evidence.

Skill by Sertxito

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/sertxito-ai-platform-audit

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Review AI, retrieval, agent, and MCP systems for grounding, evaluation, permissions, privacy, observability, and cost evidence.

Use cases: security, agent-building

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/ai-platform-audit

What's inside

Skill name
ai-platform-audit
Description
Review AI, retrieval, agent, and MCP systems for grounding, evaluation, permissions, privacy, observability, and cost evidence.
License
MIT
Instructions
20 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# AI platform audit

## Procedure
1. Map model, retrieval, ingestion, tools, memory, users, trust boundaries, and
   data flows.
2. Inspect grounding sources, freshness, access trimming, evaluation sets, and
   observed quality evidence.
3. Review tool permissions, prompt-injection boundaries, approval behavior,
   retention, and cross-user/session isolation.
4. Inspect latency, failure, cost, and audit signals; mark absent measurements
   as unknown rather than assigning maturity scores.
5. Define representative positive, ambiguous, unavailable-tool, and adversarial
   evaluations with explicit oracles.

## Output
Evidence-backed risks, coverage limits, evaluation gaps, and prioritized
verification. Do not claim zero hallucinations, safety, or maturity without
measured and reviewed evidence.

From Sertxito/mcp-efficiency-engine, MIT.

More from Sertxito/mcp-efficiency-engine

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Last commit (this folder)
Oct 19, 2026 (9 days ago)
Last release
Oct 22, 2026 (6 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from Sertxito

Cite this page

ai-platform-audit skill. Agent Mart. https://agentmart.dev/skills/sertxito-ai-platform-audit (last updated 2026-10-24)